19 citations · 24 across the 13 of their papers we have counts for
4 papers · 1 filter
Relational Task Generation Language: A Declarative Specification Framework for Relational Deep Learning
Oleksii Kolesnichenko, Jakub Peleška, Gustav Š\'ır
Relational Deep Learning (RDL) has become a powerful paradigm for learning from multi-tabular data. However, manually defining RDL prediction tasks is a laborious process that freq…
Incremental Evaluation and Training in Relational Deep Learning
Jakub Peleška, Gustav Šír
Relational Deep Learning (RDL) models multi-tabular databases as temporal heterogeneous graphs to enable end-to-end representation learning. However, prevailing RDL evaluation prac…
Universal Encoders for Modular Relational Deep Learning
Jakub Peleška, Gustav Šír
Relational Deep Learning (RDL) models multi-tabular databases as temporal heterogeneous graphs for end-to-end representation learning. While RDL is evolving rapidly, existing appro…
Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modelling
Danial Hooshyar, Gustav Šír, Yeongwook Yang +6
The growing use of artificial intelligence (AI) in education, particularly large language models (LLMs), has increased interest in intelligent tutoring systems. However, LLMs often…